Inductive Synthesis of Functional Programs [electronic resource] :Universal Planning, Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning /
Contributor(s): SpringerLink (Online service).Material type: BookSeries: Lecture Notes in Computer Science: 2654Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2003.Description: XXII, 402 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540448464.Subject(s): Computer science | Science | Computer programming | Software engineering | Computer logic | Mathematical logic | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Science, general | Programming Techniques | Software Engineering | Logics and Meanings of Programs | Mathematical Logic and Formal LanguagesOnline resources: Click here to access online
1. Introduction -- 1. Introduction -- I. Planning -- 2. State-Based Planning -- 3. Constructing Complete Sets of Optimal Plans -- 4. Integrating Function Application in State-Based Planning -- 5. Conclusions and Further Research -- II. Inductive Program Synthesis -- 6. Automatic Programming -- 7. Folding of Finite Program Terms -- 8. Transforming Plans into Finite Programs -- 9. Conclusions and Further Research -- III. Schema Abstraction -- 10. Analogical Reasoning and Generalization -- 11. Structural Similarity in Analogical Transfer -- 12. Programming by Analogy -- 13. Conclusions and Further Research.
Because of its promise to support human programmers in developing correct and efficient program code and in reasoning about programs, automatic program synthesis has attracted the attention of researchers and professionals since the 1970s. This book focusses on inductive program synthesis, and especially on the induction of recursive functions; it is organized into three parts on planning, inductive program synthesis, and analogical problem solving and learning. Besides methodological issues in inductive program synthesis, emphasis is placed on its applications to control rule learning for planning. Furthermore, relations to problem solving and learning in cognitive psychology are discussed.